Chest trauma accounts for 20% of all trauma cases in the world. Chest trauma is estimated to be the primary cause of death in 25% of traumatic mortalities and a contributing factor in another 25% of deaths. Early detection and timely selection of the appropriate investigations and treatments are all critical components for optimal outcome. Ultrasound imaging is widely used for the initial diagnosis to evaluate patients with blunt thoracic trauma. Identifying or detecting pneumothorax (PTX) is critically important in making an accurate diagnosis and is considered a key feature to be detected.
At present, PTX detection approaches using ultrasound are based on visual observations of images following the Bedside Lung Ultrasound in Emergency (BLUE or its updated version) protocol, which are time consuming and dependent on operators' experiences. For inexperienced ultrasound operators, the detecting sensitivity is only 57%, compared to 91% for well-trained and experienced operators. The ultrasound detection of PTX is the most difficult part of training: much experience is required to acquire appropriate skills to recognize lung sliding and its abolition. The detection is even more difficult in the presence of partial PTX or small PTX. The patient should lie strictly supine to allow location of pleural gas effusion in non-dependent lung regions. The major problem for detecting PTX via ultrasound is the need for advanced training, and its accuracy is highly operator dependent.
WO 2006/044996 A2 discloses system and method for the automatic detection of the boundary of a structure in an ultrasound image. The method includes providing a matrix of pixel values corresponding to the image. An autocorrelation calculation is performed on the matrix of pixel values to generate a new, correlation matrix to emphasize the difference in echogenicity between the structure and the surrounding image.